Robust Bayesian hierarchical modeling and inference using scale mixtures of normal distributions
Sign Up to like & getrecommendations! Published in 2021 at "IISE Transactions"
DOI: 10.1080/24725854.2021.1912440
Abstract: Abstract Empirical models that relate multiple quality features to a set of design variables play a vital role in many industrial process optimization methods. Many of the current modeling methods employ a single-response normal model… read more here.
Keywords: bayesian hierarchical; inference using; modeling inference; hierarchical modeling ... See more keywords
Understanding the Constraints in Maximum Entropy Methods for Modeling and Inference
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Pattern Analysis and Machine Intelligence"
DOI: 10.1109/tpami.2022.3185394
Abstract: The principle of maximum entropy, developed more than six decades ago, provides a systematic approach to modeling inference, and data analysis grounded in the principles of information theory, Bayesian probability and constrained optimization. Since its… read more here.
Keywords: modeling inference; understanding constraints; maximum entropy; constraints maximum ... See more keywords
Mathematical Modeling and Inference of Epidermal Growth Factor-Induced Mitogen-Activated Protein Kinase Cell Signaling Pathways
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DOI: 10.3390/ijms251810204
Abstract: The mitogen-activated protein kinase (MAPK) pathway is an important intracellular signaling cascade that plays a key role in various cellular processes. Understanding the regulatory mechanisms of this pathway is essential for developing effective interventions and… read more here.
Keywords: mitogen activated; activated protein; protein kinase; modeling inference ... See more keywords